The Data Provenance Initiative is a multi-disciplinary volunteer effort to improve transparency, documentation, and responsible use of training datasets for AI. Through a large scale audit of 44 data ...
Abstract: In this paper, we leverage unmanned aerial vehicles (UAVs) to enhance mobile crowd sensing (MCS) by addressing two critical challenges: uncontrollable data quality and inevitable unsensed ...
Digital research platforms can be used to increase participant access, improve study engagement, streamline data collection, and increase data quality; however, the efficacy and sustainability of ...
Abstract: Sparse crowdsensing collects data from a subset of the sensing area and infers data for unsensed areas, reducing data collection costs. Previous works have primarily focused on independently ...
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